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Changes in chromatin accessibility in intratumoral CD8+ T cell subsets between young and aged TME

GSE255230 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 38 samples Submitted 2024/03/14 Platform GPL32159Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 38 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
38 samples: 38 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
The aged tumor microenvironment limits T cell control of cancerNature immunology · 2024
Summary (written by the submitters)
Here, we present genome-wide comparisons of chromatin accessibility from endogenous CD8+ T cells and transferred OT-1 CD8+ T cells in young vs. aged B16-OVA tumors using ATAC-seq. This ATAC-seq dataset includes three different intratumoral CD8+ T cell subsets, such as TProg: Slamf6+Tim-3-, TTerm: Slamf6-Tim-3+, and TTAD: Slamf6-Tim-3-, as well as naive CD8+ T cells from spleens.
Published in
The aged tumor microenvironment limits T cell control of cancer
Chen ACY, Jaiswal S, Martinez D et al. · Nature immunology 2024 · PMID 38745085 · doi:10.1038/s41590-024-01828-7
This dataset
Open GSE255230 in finder → Find more mouse ChIP / ATAC / CUT&Tag datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE255230_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1074054 and SRA study SRP488564. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38745085) ↗
Study design
38 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 38 sample titles: 38 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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